DIGGING DEEPER INTO THE 10 BIG IDEAS
Table of Contents
Introduction
The 10 Big Ideas
Digging Deeper
- Measure what matters to workers, capturing a full range of job quality indicators
- Center equity in measurement
- Increase mandatory human capital data disclosure
- Link public and private data to gain new insights into the quality of jobs
- Leverage business data to demonstrate the return on investment from good jobs
- Revise data systems to include and support the non-W2 workforce
- Strengthen workforce system metrics to deliver results for workers and businesses
- Use public and private spending to measure and strengthen equity and good jobs
- Strengthen state and local capacity for data-driven decision-making to advance good jobs
- Invest in strengthening job quality measurement
Understanding the Impact
Appendices
Acknowledgements
#9: Strengthen state and local capacity for data-driven decision making to advance good jobs.
These actions are intended for…
A collaborative, intergovernmental approach can build job quality measurement capacity at the state and local level, positioning state and local governments to design more effective, equitable workforce policies and programs.
State and local leaders care deeply about increasing equitable economic mobility but need better data infrastructure to get there. Fragmented federal program structures, aging technology, compliance-focused processes, and poorly aligned incentives have hindered states and localities from investing in the robust data capacity needed to drive innovation in workforce development and other social service programs. With support from federal agencies and philanthropy, state and local governments can accelerate job quality measurement and improve service delivery and outcomes.
To put this into practice and support state and local government to strengthen job quality measurement, federal agencies and philanthropy can:
1. Build state and local capacity to measure job quality and equity.
Federal government incentives and supports provide important tools as state and local agencies grapple with growing needs amidst staffing shortages and lingering pandemic impacts. Coupling clear federal guidance with funding, flexibility, and technical assistance will accelerate local efforts to strengthen job quality measurement.
JQMI members recommended that federal agency leaders partner with state and local government and philanthropy, including:
- The White House Office of Management and Budget (OMB) can partner with the The U.S. Department of Labor (DOL), the U.S. Department of Health and Human Services (HHS), and other federal agencies to outline mechanisms to braid funding from multiple federal funding streams to support shared data infrastructure, analysis, research and associated staff development to advance job quality goals. For example, Indiana and Ohio have created modern, integrated data hubs and analytics capacity that integrate and analyze data from labor, education, and health and human services programs using pooled funds from federal grant programs. OMB and federal agencies should provide joint guidance on permissible investments in hardware, software and staff training which will enable an agency both to carry out its own research and to make their data more useful for external parties. Ultimately, state and local agencies must be positioned to tap into data analytics, computer science, and machine learning expertise to tackle some of their most challenging needs.
- DOL and OMB should partner to provide additional flexibility and relief from certain compliance reporting for jurisdictions that can accurately report key job quality outcome metrics, disaggregated by subpopulations (e.g. using the exception authority in 2 CFR 100.102(d), OMB’s government-wide grant regulations) as a powerful way to ensure local jurisdictions are allocating resources to building data analytics capacity. Such flexibility should also be paired with technical assistance from peer networks on leading practices to expand local area knowledge and networks.
- DOL can model using their funding processes to drive both local data capacity development and coordination by requiring that new federal investments in state or local information technology systems (e.g. Unemployment Insurance Modernization) only be awarded for interoperable systems that will make data accessible for research purposes, consistent with principles established by the Evidence Act. 1 Preference could also be given in grant competitions for jurisdictions that will use a portion of their funds for data analysis and evaluation, including investment in re-usable infrastructure.
- DOL should give recognition, such as awards to high performing workforce boards or unrestricted funding grants, to jurisdictions that make significant progress in using data and evidence to improve workforce programs and/or make significant advancements in establishing interagency data sharing, especially for successful state and local efforts that expand the reach of workforce initiatives to include social services, justice involvement, immigration, and other relevant areas.
- Philanthropy can support this state and local perspective reset from “whether to share” to “how to share” by funding innovative data analytics pilots, investing in technology infrastructure, and using grant processes to incentivize the expansion of staff data analytics, visualization, and processing skills. This can include a mix of place-based investments to build capabilities in a particular region, indirect rate flexibilities to support infrastructure development and incentives for programs with a demonstrated ability to leverage cross agency data collaborations. Across investments, philanthropy can support government partners to prioritize participant privacy and consent to build trust and advance equity.
2. Launch an Intergovernmental Research and Analytics Consortium dedicated to advancing good jobs.
DOL has made important strides in increasing the capacity of state Labor Market Information staff through multiple efforts, including the Bureau of Labor Statistics Federal-State Occupational Employment and Wage Statistics (OEWS) program. In addition, existing regional research collaboratives supported by philanthropy have helped to build government capacity. Building on these efforts, DOL should create an Intergovernmental Research and Analytics Consortium with a select group of state and local jurisdictions that partner with researchers and data scientists to produce rigorous studies using linked administrative data.
To build capacity of state and local government staff, DOL can partner with other federal agencies to:
- Select a group of high-capacity state and local jurisdictions, and support them to collaborate on shared research priorities and implementation strategies, including learning agendas, research designs, privacy-protecting data-linkage methods and, when appropriate, multi-site trials, in collaboration with researchers. Explore ways to leverage infrastructure and recovery funding to resource and begin testing this work. Prioritize these high-capacity jurisdictions for participation in federal pilots centered on equity and job quality measurement, to develop efficient, privacy-protecting mechanisms for merging state and local data with federal data—including earnings and other data held by federal agencies that support or track training and job quality, including HHS, the Internal Revenue Service (IRS), the U.S. Department of Commerce (DOC), the U.S. Department of Justice (DOJ), U.S. the Department of Education (DOE), the U.S. Department of Agriculture (DOA), the National Science Foundation (NSF), and the U.S. Census Bureau.
- Support states in the Consortium that collect hours and occupational data in their Unemployment Insurance (UI) wage records systems to conduct pilots to develop better measures of job quality, which would inform future changes in other state UI systems or to federal data requirements in accordance with Idea #4. Local jurisdictions could generate valuable insights on regional job quality issues, such as work by New York City’s Office of Labor Policy and Standards which focuses on key workplace laws such as paid sick leave and fair workweek. The office currently uses administrative data coupled with worker complaint filings to protect the rights of care workers, support business compliance, and advance new policy initiatives that strengthen protections for workers facing high risk of violations, who are disproportionately people of color, women, and immigrants.
Endnotes
- Office of the Assistant Secretary for Planning and Evaluation. Implementing the Foundations for Evidence-Based Policymaking Act at the U.S. Department of Health & Human Services.